Summary:
Analysis of multi-parameter data allows using an array of independent and quantifiable information on the physical properties of a particular geological object to create a search pattern. So geological objects with known properties and a created search pattern can apply to recognize the geological formations of a similar composition, genesis or structure. From these positions, the importance of the petrophysical classifier is supposed to detect useful aspects of geological objects by statistical processing. Attempts to develop a multidimensional classifier based on the most common and relatively simple construction of linear regression equations did not succeed, as the sign components of the regression function were very small. Then we present an example of the joint use of the method of Principal Components & Classification Analysis (PCCA) and the discriminant function analysis (DFA) for the creation of a classifier of petrotypes.
We used a data on the physical properties of 27 petrotypes of the Ingul region of Ukrainian Shields:
1) findings of the most informative petrophysical parameter to detection of local areas with given physical and technical properties (PCCA);
2) grouping all the petrotypes into separate groups (in this case the maximum homogeneity of the group and the minimum - between the groups are reached (PCCA);
3) setting discriminant levels of group separation and development a classification rule (DFA).
A 2-rank system of informative ability of a complex of petrophysical parameters, a 4-group structure of separation of petrotypes and a dichotomous nature of a petrophysical classifier with discriminator coefficients are established.